Observer Based Adaptive Fault-Tolerant Control of Switched Nonlinear Systems
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- 英文论文题名：Observer Based Adaptive Fault-Tolerant Control of Switched Nonlinear Systems
- 论文作者：Li Tang ; Jun Zhao ; Georgi M.Dimirovski ; Lei Liu
- 英文论文作者：Li Tang ; Jun Zhao ; Georgi M.Dimirovski ; Lei Liu ; State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University) ; College of Information Science and Engineering ; Northeastern University ; School of Engineering ; Dogus University
- 年：2017
- 作者机构：State Key Laboratory of Synthetical Automation for Process Industries (Northeastern University),College of Information Science and Engineering,Northeastern University;School of Engineering,Dogus University;
- 英文论文关键词：Fault-Tolerant Control ; Nonlinear Observer ; Dynamic Surface Control ; Switched Nonlinear Systems ; Average Dwell Time
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TP273
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：6
- 文件大小：615k
- 原文格式：D
- 会议级别：全国
摘要
An adaptive fault-tolerant control strategy is proposed for a class of switched nonlinear systems with unknown functions and unavailable states by using the improved average dwell time technique and backstepping method. We use radial basis function neural networks(RBFNNs) to approximate the unknown functions and a switched nonlinear state observer is designed to estimate the unavailable states. In order to solve the explosion of the complexity problem, dynamic surface control technique is used. The presented fault-tolerant controllers and update laws guarantee the boundedness of all signals in the closed-loop system under a class of switching signals with average dwell time. Furthermore, the system output can track a given reference signal and the estimation errors converge to some small compact sets. Finally, an example is employed to illustrate the effectiveness of the proposed method.
An adaptive fault-tolerant control strategy is proposed for a class of switched nonlinear systems with unknown functions and unavailable states by using the improved average dwell time technique and backstepping method. We use radial basis function neural networks(RBFNNs) to approximate the unknown functions and a switched nonlinear state observer is designed to estimate the unavailable states. In order to solve the explosion of the complexity problem, dynamic surface control technique is used. The presented fault-tolerant controllers and update laws guarantee the boundedness of all signals in the closed-loop system under a class of switching signals with average dwell time. Furthermore, the system output can track a given reference signal and the estimation errors converge to some small compact sets. Finally, an example is employed to illustrate the effectiveness of the proposed method.
An adaptive fault-tolerant control strategy is proposed for a class of switched nonlinear systems with unknown functions and unavailable states by using the improved average dwell time technique and backstepping method. We use radial basis function neural networks(RBFNNs) to approximate the unknown functions and a switched nonlinear state observer is designed to estimate the unavailable states. In order to solve the explosion of the complexity problem, dynamic surface control technique is used. The presented fault-tolerant controllers and update laws guarantee the boundedness of all signals in the closed-loop system under a class of switching signals with average dwell time. Furthermore, the system output can track a given reference signal and the estimation errors converge to some small compact sets. Finally, an example is employed to illustrate the effectiveness of the proposed method.
引文
[1]X.Zhao,Y.Yin,B.Niu,and X.Zheng,Stabilization for a class of switched nonlinear systems with novel average dwell time switching by T-S fuzzy modeling,IEEE Transactions on Cybernetics,46(8):1952–1957,2016.
[2]J.Zhao,and D.Hill,Dissipativity theory for switched systems,IEEE Transactions on Automatic Control,53(4):941–953,2008.
[3]Y.Li,S.Sui,and S.Tong,Adaptive fuzzy control design for stochastic nonlinear switched systems with arbitrary switchings and unmodeled dynamics,IEEE Transactions on Cybernetics,DOI:10.1109/TCYB.2016.2518300,2016.
[4]H.Zhang,D.Xie,H.Zhang,and G.Wang,Stability analysis for discrete-time switched systems with unstable subsystems by a mode-dependent average dwell time approach,Isa Transactions,53(4):1081–1086,2014.
[5]L.Tang,and J.Zhao,Neural network based adaptive prescribed performance control for a class of switched nonlinear systems,Neurocomputing DOI:10.1016/j.neucom.2016.12.011,2016.
[6]J.Fu,R.Ma,and T.Chai,Global finite-time stabilization of a class of switched nonlinear systems with the powers of positive odd rational numbers,Automatica,54:360–373,2015.
[7]J.Xiong,J.Lam,Z.Shu,and X.Mao,Stability analysis of continuous-time switched systems with a random switching signal,IEEE Transactions on Automatic Control,59(1):180–186,2014.
[8]D.Liberzon,Switching in Systems and Control.Berlin,Germany:Springer-Verlag,2003,chapter 2.
[9]L.Hao,and G.Yang,Robust adaptive fault-tolerant control of uncertain linear systems via sliding-mode output feedback,International Journal of Robust and Nonlinear Control,25(14):2461–2480,2014.
[10]Z.Gao,and S.Ding,Actuator fault robust estimation and fault-tolerant control for a class of nonlinear descriptor systems,Automatica,43(5):912–920,2007.
[11]Y.Diao,and K.Passino,Intelligent fault-tolerant control using adaptive and learning methods,Control Engineering Practice,10(8):801–817,2002.
[12]L.Liu,Z.Wang,and H.Zhang,Adaptive NN fault-tolerant control for discrete-time systems in triangular forms with actuator fault,Neurocomputing,152(25):209–221,2015.
[13]L.Liu,Z.Wang,and H.Zhang,Adaptive fault-tolerant tracking control for MIMO discrete-time systems via reinforcement learning algorithm with less learning parameters,IEEE Transactions on Automation Science and Engoneering,DOI:10.1109/TASE.2016.2517155,2016.
[14]Q.Shen,and B.Jiang,Novel networks-based fault tolerant control scheme with fault alarm,IEEE Transactions on Cybernetics,44(11):2190–2201,2014.
[15]L.Long,and J.Zhao,Adaptive ouput-feedback neural control of switched uncertain nonlinear systems with average dwell time,IEEE Transactions on Neural Networks and Learning Systems,26(7):1350–1362,2015.
[16]W.Dong,J.Farrell,M.Polycarpou,V.Djapic,and M.Sharma,Command filtered adaptive backstepping,IEEE Transactions on Control Systems Technology,20(3):566–580,2012.
[2]J.Zhao,and D.Hill,Dissipativity theory for switched systems,IEEE Transactions on Automatic Control,53(4):941–953,2008.
[3]Y.Li,S.Sui,and S.Tong,Adaptive fuzzy control design for stochastic nonlinear switched systems with arbitrary switchings and unmodeled dynamics,IEEE Transactions on Cybernetics,DOI:10.1109/TCYB.2016.2518300,2016.
[4]H.Zhang,D.Xie,H.Zhang,and G.Wang,Stability analysis for discrete-time switched systems with unstable subsystems by a mode-dependent average dwell time approach,Isa Transactions,53(4):1081–1086,2014.
[5]L.Tang,and J.Zhao,Neural network based adaptive prescribed performance control for a class of switched nonlinear systems,Neurocomputing DOI:10.1016/j.neucom.2016.12.011,2016.
[6]J.Fu,R.Ma,and T.Chai,Global finite-time stabilization of a class of switched nonlinear systems with the powers of positive odd rational numbers,Automatica,54:360–373,2015.
[7]J.Xiong,J.Lam,Z.Shu,and X.Mao,Stability analysis of continuous-time switched systems with a random switching signal,IEEE Transactions on Automatic Control,59(1):180–186,2014.
[8]D.Liberzon,Switching in Systems and Control.Berlin,Germany:Springer-Verlag,2003,chapter 2.
[9]L.Hao,and G.Yang,Robust adaptive fault-tolerant control of uncertain linear systems via sliding-mode output feedback,International Journal of Robust and Nonlinear Control,25(14):2461–2480,2014.
[10]Z.Gao,and S.Ding,Actuator fault robust estimation and fault-tolerant control for a class of nonlinear descriptor systems,Automatica,43(5):912–920,2007.
[11]Y.Diao,and K.Passino,Intelligent fault-tolerant control using adaptive and learning methods,Control Engineering Practice,10(8):801–817,2002.
[12]L.Liu,Z.Wang,and H.Zhang,Adaptive NN fault-tolerant control for discrete-time systems in triangular forms with actuator fault,Neurocomputing,152(25):209–221,2015.
[13]L.Liu,Z.Wang,and H.Zhang,Adaptive fault-tolerant tracking control for MIMO discrete-time systems via reinforcement learning algorithm with less learning parameters,IEEE Transactions on Automation Science and Engoneering,DOI:10.1109/TASE.2016.2517155,2016.
[14]Q.Shen,and B.Jiang,Novel networks-based fault tolerant control scheme with fault alarm,IEEE Transactions on Cybernetics,44(11):2190–2201,2014.
[15]L.Long,and J.Zhao,Adaptive ouput-feedback neural control of switched uncertain nonlinear systems with average dwell time,IEEE Transactions on Neural Networks and Learning Systems,26(7):1350–1362,2015.
[16]W.Dong,J.Farrell,M.Polycarpou,V.Djapic,and M.Sharma,Command filtered adaptive backstepping,IEEE Transactions on Control Systems Technology,20(3):566–580,2012.